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Linguistic resources for paraphrase generation in Portuguese: a Lexicon-Grammar approach
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In: ISSN: 1574-020X ; EISSN: 1574-0218 ; Language Resources and Evaluation ; https://hal.archives-ouvertes.fr/hal-03548861 ; Language Resources and Evaluation, Springer Verlag, 2022, ⟨10.1007/s10579-021-09561-5⟩ ; https://link.springer.com/article/10.1007/s10579-021-09561-5 (2022)
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| 2 |
Un cas d'école : le participe passé à hue et à dia
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In: Accord Non-Accord ; https://hal.archives-ouvertes.fr/hal-03603479 ; Catherine Collin. Accord Non-Accord, Presses Universitaires de Rennes, pp.267-286, 2022 (2022)
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Förderung des Bildungsspracherwerbs bei heterogenen sprachlichen Voraussetzungen im Unterricht mit digitalen Medien ...
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Proportionate translation of study materials and measures in a multinational global health trial: methodology development and implementation ...
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| 6 |
Enhancing Linguistic and Cultural Learning during Education Abroad in Japan
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| 7 |
Sprachliche Individualisierung mittels digitaler Medien
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In: Haider, Michael [Hrsg.]; Schmeinck, Daniela [Hrsg.]: Digitalisierung in der Grundschule. Grundlagen, Gelingensbedingungen und didaktische Konzeptionen am Beispiel des Fachs Sachunterricht. Bad Heilbrunn : Verlag Julius Klinkhardt 2022, S. 140-153 (2022)
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| 8 |
Förderung des Bildungsspracherwerbs bei heterogenen sprachlichen Voraussetzungen im Unterricht mit digitalen Medien
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In: Haider, Michael [Hrsg.]; Schmeinck, Daniela [Hrsg.]: Digitalisierung in der Grundschule. Grundlagen, Gelingensbedingungen und didaktische Konzeptionen am Beispiel des Fachs Sachunterricht. Bad Heilbrunn : Verlag Julius Klinkhardt 2022, S. 124-139 (2022)
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| 10 |
Evangelical Mental Health During A Pandemic: A Three-Way Interaction Analysis
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In: Doctoral Dissertations and Projects (2022)
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| 11 |
Linking COVID-19-Related Awareness and Anxiety as Determinants of Coping Strategies’ Utilization among Senior High School Teachers in Cape Coast Metropolis, Ghana
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In: Social Sciences; Volume 11; Issue 3; Pages: 137 (2022)
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| 12 |
The Role of Perceived Social Support and Stress in the Relationship between Hope and Depression among Chinese Shadow Education Tutors: A Serial Mediation Model
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In: International Journal of Environmental Research and Public Health; Volume 19; Issue 6; Pages: 3348 (2022)
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| 13 |
Advancements in Oncology with Artificial Intelligence—A Review Article
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In: Cancers; Volume 14; Issue 5; Pages: 1349 (2022)
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| 14 |
Identity Distress among Immigrant Students during COVID-19
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In: Societies; Volume 12; Issue 2; Pages: 29 (2022)
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| 15 |
A Comparative Review on Applications of Different Sensors for Sign Language Recognition
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In: Journal of Imaging; Volume 8; Issue 4; Pages: 98 (2022)
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| 16 |
Probabilistic Linguistic Matrix Game Based on Fuzzy Envelope and Prospect Theory with Its Application
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In: Mathematics; Volume 10; Issue 7; Pages: 1070 (2022)
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| 17 |
Journal of College Academic Support Programs, Volume 3, Issue 1, Spring/Summer 2020
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In: Journal of College Academic Support Programs, Spring/Summer 2020, Vol. 3, No. 1. (2022)
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| 18 |
Robust phoneme recognition for a speech therapy environment
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| 19 |
Detecting weak and strong Islamophobic hate speech on social media
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Abstract:
Islamophobic hate speech on social media is a growing concern in contemporary Western politics and society. It can inflict considerable harm on any victims who are targeted, create a sense of fear and exclusion amongst their communities, toxify public discourse and motivate other forms of extremist and hateful behavior. Accordingly, there is a pressing need for automated tools to detect and classify Islamophobic hate speech robustly and at scale, thereby enabling quantitative analyses of large textual datasets, such as those collected from social media. Previous research has mostly approached the automated detection of hate speech as a binary task. However, the varied nature of Islamophobia means that this is often inappropriate for both theoretically informed social science and effective monitoring of social media platforms. Drawing on in-depth conceptual work we build an automated software tool which distinguishes between non-Islamophobic, weak Islamophobic and strong Islamophobic content. Accuracy is 77.6% and balanced accuracy is 83%. Our tool enables future quantitative research into the drivers, spread, prevalence and effects of Islamophobic hate speech on social media. ; Engineering and Physical Sciences Research Council
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Keyword:
Big data; Communication; Hate speech; Islamophobia; Machine learning; Natural language processing; Prejudice; Scale; Science; Social media; Support; Twitter
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URL: https://doi.org/10.1080/19331681.2019.1702607
http://hdl.handle.net/10197/12720
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| 20 |
A Visual Decision-Support System using Fingerprint Matrices applied to Cyclical Spatio-Temporal Data from Motorsports
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